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Dynamical functional prediction and classification, with application to traffic flow prediction. (English) Zbl 1257.62090

Summary: Motivated by the need for accurate traffic flow prediction in transportation management, we propose a functional data method to analyze traffic flow patterns and predict future traffic flow. We approach the problem by sampling traffic flow trajectories from a mixture of stochastic processes. The proposed functional mixture prediction approach combines functional prediction with probabilistic functional classification to take distinct traffic flow patterns into account. The probabilistic classification procedure, which incorporates functional clustering and discrimination, hinges on subspace projection. The proposed methods not only assist in predicting traffic flow trajectories, but also identify distinct patterns in daily traffic flow of typical temporal trends and variabilities. The proposed methodology is widely applicable in analysis and prediction of longitudinally recorded functional data.

MSC:

62M20 Inference from stochastic processes and prediction
90B06 Transportation, logistics and supply chain management
62H30 Classification and discrimination; cluster analysis (statistical aspects)
90B20 Traffic problems in operations research
62M99 Inference from stochastic processes

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References:

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